Stable isotope composition of walleye: <sup>15</sup>N accumulation with age and area-specific differences in δ<sup>13</sup>C
Bibliographic record
Abstract
Stable nitrogen and carbon isotope ratios were measured for walleye (Stizostedion vitreum) collected across Lake Champlain, Vermont, to determine relationships between isotopic composition and diet, location of capture, length, weight, and age. Variation in δ13C values reflected area-specific differences in isotopic composition of organisms collected across the lake. A critical assumption in the application of isotope techniques is that a predictable relationship exists between the diet and isotopic composition of an organism. Our results indicate that isotopic fractionation factors may not be independent of age as has largely been assumed. By combining stable nitrogen and carbon isotope analysis with conventional stomach content analysis, we documented significant age effects in the δ15N composition of adult walleye that were not attributable to observed changes in diet. Age accounted for 81% of the variation in δ15N values of walleye (ages 227, N = 65, δ15N range = 15.319.2), providing evidence supporting 15N accumulation over the life span of walleye. Therefore, the risk of making faulty inferences of trophic position and food web interactions based on δ15N values may be increased when age is unknown. Our results indicate that metabolic effects associated with age require greater consideration in applications of stable isotope analysis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".